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From Robert Metzger <rmetz...@apache.org>
Subject Re: How to achieve exactly once on node failure using Kafka
Date Thu, 23 Feb 2017 16:08:48 GMT
Hi,

exactly. You have to make sure that you can write data for the same ID
multiple times.
Exactly once in Flink is only guaranteed for registered state. So if you
have a flatMap() with a "counter" variable, that is held in a "ValueState",
this counter will always be in sync with the number of elements in the
kafka topic (because the counter is reset on a failure).

On Tue, Feb 21, 2017 at 4:04 PM, Y. Sakamoto <phonypianist@gmail.com> wrote:

> Thank you for your reply.
>
> Under my understanding, Map / Filter Function operate with "at least once"
> when a failure occurs, and it is necessary to code that it will be saved
> (overwritten) in Elasticsearch with the same ID even if double data comes.
> Is it correct?
> (sorry, I cannot understand how to "write changes to Flink's state to
> Elastic")
>
> Regards,
> Yuichiro
>
>
> On 2017/02/21 3:56, Stephan Ewen wrote:
>
>> Hi!
>>
>> Exactly-once end-to-end requires sinks that support that kind of behavior
>> (typically some form of transactions support).
>>
>> Kafka currently does not have the mechanisms in place to support
>> exactly-once sinks, but the Kafka project is working on that feature.
>> For ElasticSearch, it is also not simply possible (because of missing
>> transactions), but you can use Flink's state as the "authorative" state (it
>> is exactly once) and then write changes to Flink's state to Elastic. That
>> way the writes to ElasticSearch become "idempotent", which means duplicates
>> simple make no additional changes.
>>
>> Hope that helps!
>>
>> Stephan
>>
>>
>>
>>
>> On Mon, Feb 20, 2017 at 5:53 PM, Y. Sakamoto <phonypianist@gmail.com
>> <mailto:phonypianist@gmail.com>> wrote:
>>
>>     Hi,
>>     I'm using Flink 1.2.0 and try to do "exactly once" data transfer
>>     from Kafka to Elasticsearch, but I cannot.
>>     (Scala 2.11, Kafka 0.10, without YARN)
>>
>>     There are 2 Flink TaskManager nodes, and when processing
>>     with 2 parallelism, shutdown one of them (simulating node failure).
>>
>>     Using flink-connector-kafka, I wrote following code:
>>
>>        StreamExecutionEnvironment env = StreamExecutionEnvironment
>>              .getExecutionEnvironment();
>>        env.enableCheckpointing(1000L);
>>        env.setParallelism(2);
>>
>>        Properties kafkaProp = new Properties();
>>        kafkaProp.setProperty("bootstrap.servers", "192.168.97.42:9092 <
>> http://192.168.97.42:9092>");
>>        kafkaProp.setProperty("zookeeper.connect", "192.168.97.42:2181 <
>> http://192.168.97.42:2181>");
>>        kafkaProp.setProperty("group.id <http://group.id>", "id");
>>
>>        DataStream<String> stream = env.addSource(new
>> FlinkKafkaConsumer010<>(
>>              "topic", new SimpleStringSchema(), kafkaProp));
>>
>>     I found duplicated data transfer on map function.
>>     Data from the checkpoint before node failure seems duplicated.
>>
>>     Is there any way to achieve "exactly once" on failure?
>>
>>
>>     Thanks.
>>     Yuichiro
>>
>>
>>
>
> --
> ☆ ─────────────── ─ ─ - -
> Yuichiro SAKAMOTO
> ksooj@muc.biglobe.ne.jp
> phonypianist@gmail.com
> http://phonypianist.sakura.ne.jp
>
>

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